{"id":"W2337800828","doi":"","title":"XV Апрельская международная научная конференция НИУ ВШЭ «Модернизация экономики и общества». Семинар «Долгосрочное прогнозирование науки, технологий и инноваций: вызовы для научно-технической политики» (2-3 апреля 2014 года)","year":2014,"lang":"ru","type":"article","venue":"Foresight-Russia","topic":"Scientific Research and Philosophical Inquiry","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"category_scores_codex":[0.01015431,0.004135923,0.004144054,0.00279599,0.004306436,0.006552081,0.01637169,0.002960334,0.009058799],"category_scores_gemma":[0.002465819,0.003688914,0.002767334,0.006170719,0.004686209,0.005056277,0.006084854,0.00595958,0.02936141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001421604,"about_ca_system_score_gemma":0.00299019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00117019,"about_ca_topic_score_gemma":0.0004660779,"domain_scores_codex":[0.9649027,0.003974203,0.005151891,0.008224229,0.008655541,0.009091428],"domain_scores_gemma":[0.9746283,0.003228964,0.002297924,0.01147673,0.001798352,0.006569688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009706504,0.001957882,0.002514004,0.001049103,0.0008121725,0.0007605017,0.003160858,0.0008226835,0.005214591,0.3622777,0.5728226,0.04763732],"study_design_scores_gemma":[0.006720271,0.003191155,0.01549148,0.001316707,0.0004780592,0.0003952345,0.0001878519,0.1329153,0.01026968,0.2667181,0.5556631,0.006653008],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1087538,0.02976467,0.3541661,0.08187982,0.07029851,0.01605001,0.002226683,0.007689367,0.3291711],"genre_scores_gemma":[0.934908,0.001547024,0.01001523,0.005299349,0.01259657,0.0006028161,0.0007551322,0.0007440728,0.03353176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8261543,"threshold_uncertainty_score":0.9983341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03689955864674127,"score_gpt":0.2880288240825896,"score_spread":0.2511292654358483,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}